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Rasmussen, Freja Nygaard; Malmqvist, Tove; Moncaster, Alice; Wiberg, Aoife Houlihan and Birgisdóttir, Harpa(2018). Analysing methodological choices in calculations of embodied energy and GHG emissions from buildings.Energy and Buildings, 158 pp. 1487–1498.

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Analysing methodological choices in calculations of embodied energy and GHG emissions from buildings

Authors

Freja Nygaard Rasmussen1*, Tove Malmqvist2, Alice Moncaster3, Aoife Houlihan Wiberg4, Harpa Birgisdóttir1

1 Danish Building Research Institute, Aalborg University, A.C Meyers Vaenge 15, 2450 Copenhagen SW, Denmark, 2

Division of Environmental Strategies Research, Department of Sustainable Development, Environmental Science and

Engineering, KTH - Royal Institute of Technology, Stockholm, Sweden ,3 Centre for Sustainable Development, University

of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK, 4 Department for Architectural Design, History and

Technology, Norwegian University of Science and Technology, NO-7465 Trondheim, Norway

*corresponding author, fnr@sbi.aau.dk

Keywords

sustainable building; life cycle assessment; embodied energy; embodied GHG emissions; methodological

choices; EN15978 standard

Abstract

The importance of embodied energy and embodied greenhouse gas emissions (EEG) from buildings is

gaining increased interest within building sector initiatives and on a regulatory level. In spite of recent

harmonisation efforts, reported results of EEG from building case studies display large variations in

numerical results due to variations in the chosen indicators, data sources and both temporal and physical

boundaries. The aim of this paper is to add value to existing EEG research knowledge by systematically

explaining and analysing the methodological implications of the quantitative results obtained, thus

providing a framework for reinterpretation and more effective comparison. The collection of over 80

international case studies developed within the International Energy Agency’s EBC Annex 57 research

programme is used as the quantitative foundation to present a comprehensive analysis of the multiple

interacting methodological parameters. The analysis of methodological parameters is structured by the

stepwise methodological choices made in the building EEG assessment practice. Each of six assessment

process steps involves one or more methodological choices relevant to the EEG results, and the

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combination potentials between these many parameters signifies a multitude of ways in which the

outcome of EEG studies are affected.

1 Introduction

Buildings are responsible for more than 40 percent of global energy used, and as much as one third of

global greenhouse gas emissions [1]. The environmental impacts from buildings are of operational as well

as embodied character, where embodied energy and greenhouse gas emissions (EEG) from buildings

concern exchanges with the environment from processes that take place in relation to the life cycle of the

building materials, for example the production processes of cement clinker which requires heating energy

and which emits CO2 from energy conversion as well as chemical processes. It is increasingly recognized

that EEG can constitute more than half of the total life cycle impacts from new buildings and is thus a key

element to address when working towards a more sustainable building sector [2].

On a regulatory level, focus from international, as well as, from regional political bodies may act as a driver

for national development of measures to reduce EEG from buildings [1][3]. Preliminary steps towards

regulatory guidelines and/or requirements are thus seen in several countries [4][5][6][7]. This regulatory

attention follows an already existing focus within the building sector itself, where voluntary initiatives

include EEG considerations as part of holistic evaluations of the sustainability of buildings, e.g. as practiced

in various certification schemes.

Furthermore, methodological improvements have been made in developing and harmonising the life cycle

assessment (LCA) method by which the EEG is quantified. Building and construction related standards

include the international standard ISO 21931-1:2010, which specifies the framework for methods of

assessment of the environmental performance of construction works, and the European standard EN

15978:2011 which specifies a calculation method for assessing the environmental performance of a

building. In parallel with the standardisation development, a number of international research projects

have focused on LCA and EEG in the building sector. These activities are carried out e.g. in a European

context [8][9][10], but also in an international context through e.g. the International Energy Agency’s

Energy in Buildings and Communities Programme (IEA-EBC). Relevant IEA-EBC research work include, most

recently, the Annex 57 on EEG in buildings (2011-2016)[11].

In spite of all the attention towards EEG and the efforts in harmonising a methodological approach,

research has pointed to the lack of consistency in the ways building LCAs are carried out, both in terms of

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system boundary definition and in terms of the indicators and the background data used for calculating the

embodied impacts [12][13][14][15]. Thus, reported EEG of buildings display large variations in numerical

results as well as inconsistent and insufficient reporting formats [16].

Knowledge on how to reduce EEG through certain design strategies can be drawn from the experiences

and analyses of the, so far, mostly individual case studies. This can guide building designers, as well as,

policy developers targeting reductions of EEG. However, it is highly important that the methodological

reasons for differences in EEG results is fully understood. Conversely, incorrect conclusions may be drawn

and used for creating and validating EEG-reducing design strategies, although these may not actually have

the desired reduction potential. Existing literature, mainly in reviews, has described methodological

parameters of importance, further explained in section 1.2. However, the parameters treated in existing

literature appear randomly sought out and thus do not provide a systematic overview that links directly to

the EEG assessment practice.

The aim of this paper is to add value to existing EEG research knowledge by systematically explaining and

analysing the methodological implications on the quantitative results obtained, thus providing a framework

for reinterpretation, more effective comparison and understanding of reduction potentials in quantitative

terms.

The systematic approach of this paper includes the consideration of the already scientifically addressed

methodological parameters, which are presented in the literature review in section 1.2. The method

section 2 introduces a structured framework for analysis based on the practical assessment process of the

EN 15978 standard. Furthermore, section 2 describes the collection of over 80 building case studies from

the IEA-EBC Annex 57 project, an international collection of EEG assessments that are reported in a

consistent and organised manner and thus provides detailed and illustrative examples of methodological

implications. The results and discussion section 3 uses the quantitative as well as the qualitative properties

of the Annex 57 case studies to analyse and empirically validate the methodological parameters that affect

the outcome of EEG studies, and the section presents a comprehensive and structured overview of these.

1.1 Defining the concept of EEG

Life cycle environmental impacts from and resource uses in buildings are often categorised as being

operational or embodied. Operational energy is intuitively understood and defined as being the energy

needed to maintain comfortable conditions in the building through processes such as heating, ventilation,

air conditioning, hot water supply, lighting or operational waste management[17][18][19]. The emissions of

energy-related pollutants from the building operation, e.g. greenhouse gasses such as CO2, can likewise be

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regarded as operational impacts [20].In contrast to the impacts related to operational energy use,

embodied energy use and greenhouse gas emissions are understood as material-related impacts, i.e. the

impacts stemming from the processes that take place in relation to the life cycle of the building materials

[21][2][22].

EEG may be sub-classified to reflect the part of the building life cycle in which they occur. Typically, this way

of classifying embodied impacts is divided into initial and recurring embodied impacts. Initial impacts signify

those related to the processes occurring up to the point in time where the building is taken into use, and

recurring impacts signify the material-related processes occurring throughout the building’s use stage, e.g.

maintenance and replacements [17][2] . Added to the initial and recurring embodied impacts are the

impacts which occur after the end of the building’s service life. These are commonly termed demolition

impacts [23][17][2], although they also cover waste treatment, transport and disposal processes as well as

impacts from the demolition processes. Some studies suggest the benefits and loads from recycling

potentials as an additional life cycle stage of importance to the life cycle impacts of a building [24][25][26].

The integration of this life cycle stage as an element of the embodied impacts however, depends on the

modelling approaches towards recycling used in the life cycle inventory of a particular study [27][28].

Consequently, results from this life cycle stage are recommended or required as reported separately from

the results of the remaining life cycle stages [26][29][30].

EEG studies of buildings display wide variations in terms of the life cycle stages included [31][32]. It can thus

be useful to distinguish between different types of system boundaries used in studies of EEG in buildings,

for instance by a cradle to gate perspective where impacts are accounted from processes only to the point

in time where the building materials are ready to leave the gate of the manufacturing facilities. The EN

15978 standard, published in 2012, presents a modular structure for defining five main life cycle stages;

production, construction, use, end of life (EoL), and finally the benefits and loads beyond the system

boundary. This modular structure can be further categorised to reflect impacts at the different types of

system boundary definitions as illustrated in Figure 1.

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Figure 1. System boundaries definitions in relation to the life cycle stages of a building [30][29][18]

1.2 Ranges of and sources for EEG variations

1.2.1 Variations of EEG results

Embodied energy use of buildings is mainly addressed in literature within the context of life cycle energy

evaluations, hence including the operational energy use in the building’s use stage. A review by Sartori and

Hestnes [33] thus found the embodied energy’s share to range between 2 and 46 % of the total life cycle

energy. Ramesh et al. [17] reviewed many of the same case studies as well as newer studies and found a

numerical range of embodied energy use between 7 and 143 kWh/m2/year. Reviews focusing on the initial

embodied energy use of buildings reports numbers in ranges between 1,500 and 19,400 MJ/m2

[34][21][35][36]. Hence, horizontal comparisons of EE studies show ranges spanning up to an approximate

factor 20.

Studies reporting ranges of EG in buildings are fewer than EE studies, but still expresses variations in the

reported ranges of results, i.e. in Hammond and Jones [21] and Hacker et al. [37] where the initial EG is

reported to vary between 228 and 606 kg CO2-eq/m2, hence an almost three-fold difference.

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As indicated from these previous reviews, the variations in results of EE and EG are profound. Part of the

variations can be explained by variations in building design, materials used, building function, etc., that is,

physical properties of the buildings, their location and use. One example is the study by Passer et al. [38]

comparing variations of building material solutions for a single family house presents ranges of 4.5 - 7 CO2-

eq/m2/year and 17 - 25 kWh/m2/year for the initial embodied impacts. These results are within a range

with maximum variations of approximately 70 % or a factor of 0.7 and thus only explains part of the 20- and

three-fold differences. Ramesh et al [17] review results distributed on building types and show practically

the same large variations within the categories of offices and residential buildings, 30-140 kWh/m2/year

and 7-143 kWh/m2/year respectively, hence pointing to building type as an inferior determinant of the

results when comparing different studies.

Thus, differences in building designs may account for some of the variations of EE and EG results presented

in literature, but the better part of the variations seem determined by the study design i.e. the

methodological choices made for the assessment. Sources for these variations are randomly described in

various literature sources which mainly focus on the indicator definitions, the background data, the

modelling approach, the system boundaries and the scenario definitions [18][12][39][2][17][40], which are

all explained in more detail in the following sections 1.2.2-1.2.6.

1.2.2 Definitions of EE and EG indicators

Embodied energy (EE) is most appropriately accounted for in its primary form, i.e. at the energy source

level before conversion, as opposed to the end-use energy at consumer [33][18]. The indicator used to

express the primary energy use (PE) is also referred to as cumulative energy demand (CED), a term that

expresses the accumulative nature of the indicator in which energy uses from different processes of the life

cycle stage are successively added. However, as described by Frischknecht et al. [41], there is no

harmonised definition of the indicator. Hence, the reported use of primary energy in a study may rely on

choices of upper or lower heating values in chemical energy resources, the energy content in uranium and

the determination of energy resource inputs of renewable energies. Furthermore, the feedstock energy,

e.g. the retained energy in petrochemical-based plastics and rubbers, is rarely reported as being included or

excluded of the primary energy indicator of building case studies [29][18][42].

There is also a range of varying definitions and considerations for the embodied greenhouse gas emissions

(EG). EG is closely related to energy since fossil or bio-based energy generation releases the greenhouse gas

(GHG) CO2, and thus the CO2 emissions related to energy use are proportional for a given fuel mix [2].

However, there are two main aspects which mean that EG is not directly proportional to EE. Firstly, EG

includes CO2 as well as other greenhouse gases, although the actual types of included greenhouse gasses

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may differ according to the chosen scope which can be e.g. the GHGs from the Kyoto protocol or the GHGs

from the latest IPCC report. Fluorocarbon gasses as regulated by the Montreal Protocol may also be

included [43]. In relation to defining the types of GHGs are also the considerations on the characterisation

factors used to express all included GHGs in CO2-equivalents and the temporal scope in which the emissions

and environmental loads are considered [13].

Secondly, EG also includes emissions of greenhouse gases from chemical and physical processes during the

life cycle of the building materials, e.g. CO2 from the cement clinker process or leakage of fluorocarbon

gasses from air condition appliances [13]. Correspondingly, building materials of biological origin, e.g. wood

products, may sequester and temporarily store CO2. There are different approaches for accounting for

biogenic carbon storage in LCA, and these can lead to large differences in the final EG results [44] [45].

1.2.3 Representativeness of background data

Representativeness of background data concerns the fundamental match between the processes included

in the building model and the background data which describes the environmental impacts of the process.

The ISO 14044:2006 data quality requirements addresses the importance of representative data at three

levels of coverage; time-related, geographical and technological coverage [46]. In relation to EEG, these

aspects are also identified as contributing to the difference in results found in several studies of applied

building LCA [12], in the comparison of different generic databases [47][40] and in the comparisons of

generic databases and environmental product declarations (EPDs) [48][49][50].However, clarification and

harmonisation is still needed, for example on aspects of system boundaries, allocation practices and service

life of products and buildings [51].

1.2.4 Modelling approaches

Two distinct modelling approaches are used in LCA practice; the input-output based and the process based.

Hybrid models based on the two are also used. The two approaches possess different strengths and

limitations in terms of completeness and accuracy [15][18]. These are reflected in reported EEG results

where input-output and hybrid based models tend to produce results in higher ranges [52].

1.2.5 System boundaries

The difference in chosen system boundaries is pinpointed in several review studies as one of the foremost

reasons for incomparability between EEG studies of buildings [18][32][17][31]. A progressive development

towards a harmonised approach in reporting the building’s life cycle stages has taken place following the

international and European standardisation efforts in this field. However, the aspect of system boundaries

is not limited to clarifying the building’s life cycle stages. Dixit et al. [39] describes how the system

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boundaries may in reality be characterised as consisting of three distinct dimensions that are all spanning

upstream and downstream processes;

1. One dimension covers the life cycle stages, e.g. extraction of raw materials or transport of materials

to building site. Some research highlights the need for simplification of the included life cycle stages

in order to limit the amount of calculation work and thus to make the LCA and EEG evaluations

implemented and used by architects and engineers as part of the building design process [10]

[53][54]. Other research points to the relevance of some life cycle stages that are often omitted

from studies, e.g. the construction stage, or the transport to site [55][56] and emphasises the

additional relevance by the timing of GHG emissions from the before-use stages [57]. Naturally, the

difference in included life cycle stages leads to difference in EEG results. However, as noted by for

instance Optis et al. [16], the simplifications of life cycle stages follow the goal and scope of the

study in question.

2. A second dimension covers the width of included inputs and outputs for each life cycle stage, e.g.

the resources used as input for the extraction of raw materials. This affects results at two levels; at

inventory level for building/building component, where e.g. omitting fixtures and fittings in some

cases may be significant [56]. Secondly, at inventory level for materials found in the applied

building material databases, where there may be differences in the number of substances and

emissions accounted for [58].

3. A third dimension that covers the physical entity being assessed, e.g. building component level or

building with site. Because this dimension indicates the scope of the study, this naturally changes

across different studies.

1.2.6 Scenario definitions

Scenario related differences found in literature focus on building level scenarios as well as material level

scenarios. For building level scenarios, studies have stressed the influence on EEG results of the building’s

estimated service life, which in turn influences the total amount of materials used for replacements etc.

Aktas and Bilec [59] refer a range of LCA studies in which the building service lives are explicitly stated as

being arbitrarily set, hence underlining the lack of a viable method to estimate a building’s life time. Several

building case studies have investigated predetermined sets of potential service lives in order to address the

sensitivity of the modelled results [60][61] or specifically focusing on the impact on results of service life

variations [62][63]. Some studies also present methodologies for addressing the combined effects of

variations in the building’s service life and variations in the service life of materials [59][64].

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Apart from the service life aspect, scenario analyses on building scale furthermore include approaches to

evaluating the significance of scenarios for single life cycle stages, e.g. scenarios for construction [65][66].

At building material level, investigations of scenario choices include those of maintenance frequencies [67],

transport [68] and EoL treatment options [25] [69][70].

2 Method

2.1 The Annex 57 case study collection

The IEA-EBC Annex 57 research work was organised into four subtasks, each focused on different aspects of

EEG in buildings[11]. Subtask 4 was responsible for identifying strategies for the reduction of EEG. In order

to do so, the subtask 4 work group collected more than 80 building case studies from the multi-national

project partners, chosen to be representative of the information on EEG currently available both in

emerging academic publications and within different national contexts [71].

The purpose of the Annex 57 case study collection was to produce a body of different detailed studies,

carried out in different countries and for different purposes, for which the relevant data was easily

accessible and identifiable. The case studies were subjected to four sequential analytical perspectives: the

impacts of methodological issues on the EEG results obtained (the focus of this paper); comparing the

impacts from different life cycle stages, materials and components; evaluating design and construction

strategies which can be used to reduce EEG from buildings; and considering the influence of geo-political,

organisational and cultural context on the measurement and reduction of EEG [72].

The initial preparatory work was the development of a systematic template, designed to allow the widest

variety of studies – including qualitative studies – whilst encouraging transparency and completeness of

quantitative data [73]. This approach enabled the comparable interpretation of the high number of

complex and detailed case studies by multiple authors. Case studies were submitted using the prepared

template, and raw data or public academic literature and reports were also made available and were

referenced within each case study description. The case studies as transcribed to the templates therefore

all report a number of specific characteristics in a consistent manner; the databases used for calculations,

the reference study period, the included life cycle stages of the assessment (based on the modular

framework of the EN 15978 standard) and the building type and location.

In spite of the template format, reported EEG results of the case study buildings were still given in a wide

variation of formats, for example from the total EG over the full building life cycle per m2 floor area per year

(kg CO2-eq/m2/year), to only the EG from the building materials production stage (cradle to gate). For

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further use in the analysis, these diversely reported results have been adjusted for the reported floor area,

reference study period and reported life cycle stages.

The case study collection spans a wide range of EEG case studies carried out for different purposes and is

valuable in the sense that it also includes examples of how building LCA is applied in practice. Hence, the

studies are not only aimed for international research and scientific publications but also contain evaluations

of EEG carried out as part of certification schemes, national research projects and academic theses.

2.2 A structure for identification of significant parameters

In order to identify and discuss the parameters causing varying EEG results in a structured manner, the

analysis of the Annex 57 case studies is based on the EN 15978 standard and the assessment process

defined therein (further specified in Table 2 of section 3.3). In contrast to the more general LCA guidance of

the ISO 14040-14044 and the ISO 21931-1, the EN 15978 focuses on a specific approach to set up a study

and calculate the potential impacts. In this sense, the standard reflects the assessor’s practice and it covers

the step-wise methodological choices that require attention in the assessment procedure [30]:

- Identify purpose of assessment

- Specification of the object of assessment

- Scenarios for the building life cycle

- Quantification of the building and its life cycle

- Selection of environmental data and other information

- Calculation of the environmental indicators

Additional, final process steps of the EN 15978 approach; “Reporting and communication” as well as

“Verification” have been left out of this analysis as they do not specifically address the assessor’s choices

regarding methodological choices in the study.

3 Results and discussion

3.1 Reported EEG results from Annex 57 case studies

The EEG results of the Annex 57 case studies are displayed in this section in order to obtain an overview of

the quantitative background results used for the analysis and discussion of methodological parameters.

This background overview includes displaying the varying ranges in results as well as the numbered case

studies which are later referred to in section 3.2 as part of the analysis. Table 1 presents a summary of the

properties of the case study collection. Appendix A provides further details of the specific case studies and

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their individual properties in terms of country of origin, the building type, databases used for calculations,

the reference study period, and the included life cycle stages of the assessment. Further qualitative details

of the case studies are specified in the case study collection report [71]. In the following analyses, specific

case studies are referred to by country and case study number, e.g. AT3.

Table 1. Summary of Annex 57 case study properties for case studies analysed in this paper

Total number of case studies 59

Study origin (country)

Austria (AT), Switzerland (CH), Germany (DE), Denmark (DK), Italy (IT), Japan (JP), South Korea (KR), Norway (NO), Sweden (SE), United Kingdom (UK)

Number of databases employed 19

Range in applied reference study period (RSP) 20-150

Number of applied system boundary combinations 18

Building types Office, residential, school

Figure 2a-b presents the ranges of and average EE and EG of selected life cycle stages reported as part of

the Annex 57 case study template. EE expresses the cases where results were explicitly reported as being

non-renewable primary energy use, i.e. CEDnren. The numbers represent new construction as well as

refurbishment projects, further detailed on case study level in Appendix A. Refurbishment cases report

numbers for all, in the refurbishment, installed materials as part of the product life cycle stages (modules

A1-A3 – refer Figure 1).

The numbers showcased in Figures 2a-b are specified for impacts within the same system boundaries (refer

Figure 1) of either product stage (A1-A3), replacements during the use stage (B4) or selected EoL processes

(C3+C4). As shown in Figures 2a-b, the ranges span profoundly, especially for the product stage EE and EG.

Reported numbers of EG range between -7 and 1,100 kg CO2-eq/m2 and reported numbers of EE range

between 943 and 12,000 MJ/m2. Note here, that the negative EG-result (-7 kg CO2-eq/m2) reflect

methodological implications of the inclusion of temporal carbon storage in wood. This is further discussed

in section 3.2.5.

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Figure 2. EE (a) and EG (b) averages and ranges from selected reported life cycle stages. Square brackets indicate number of case studies included in the displayed ranges

When adjusting results for the reference study periods used, the 41 case studies reporting product and

replacement stages range the total EG between 0.3 and 18.2 kg CO2-eq/m2/year, i.e. a 60-fold difference.

The 40 case studies reporting product and replacement stages for EE, show a range in the embodied impact

of these life cycle stages between 16 and 210 MJ/m2/year, i.e. an almost 15-fold difference.

Figure 3 displays EE and EG of the product life cycle stages, modules A1-A3, for each case study building

(refer Figure 1). Results are ordered by increasing EE and the corresponding EG, although EG results

reported without EE are also displayed in the right-hand side of the graph. Figure 3 shows how an increase

in EE seems to be followed by an increase in EG. A linear correlation analysis between the two variables EG

and EE yields an R2-value of 0.70 signifying that there is a relationship between the two indicators.

However, the relationship is not straight-forward because it reflects the multitude of underlying

methodological parameters across the studies.

0

2000

4000

6000

8000

10000

12000

14000

Product stage(A1-A3)

[43]

Replacements(B4)[40]

EoL (C3+C4)[17]

MJ/

m2

(a)

-200

0

200

400

600

800

1000

1200

Product stage(A1-A3)

[59]

Replacements(B4)[44]

EoL (C3+C4)[19]

kg C

O2-

eq

/m2

(b)

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Figure 3. EE and EG of product stage (module A1-A3) of the Annex 57 building case studies

The differences in EEG results can further be specified according to some of the reported characteristics of

each study. Figure 4a shows the EG results from the production stage (A1-A3) sorted by building use and 4b

shows the EG results sorted by five of the applied databases.

-100

100

300

500

700

900

1100

1300

0

2000

4000

6000

8000

10000

12000

14000

kg C

O2

-eq

/m2

MJ/

m2

EE (CEDnren)(MJ/m2)Production

EG(kg CO2-eq/m2)Production

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Figure 4a-b. Boxplots illustrating the distribution of EEG results from cases based on reported characteristics for building use type (4a) and database applied (4b)

Figure 4a-b shows two ways of categorising the results due to study characteristics. The figure also

highlights how some characteristics are more influent than other, in this example it shows that results

grouped by building use type reveals a variation in results although when grouped by database the

variations become even more apparent. Each of the two characterisation types are only indicators of the

specific case parameters affected; for the use type, this includes differences in building layout and material

inventory etc. For the database type, this includes differences in GWP definitions, representativeness of

data etc.

3.2 Significant methodological parameters of Annex 57 studies

In the following, the Annex 57 case studies are analysed and discussed within the framework of the

assessment process steps outlined in section 2.2.

3.2.1 Identification of the purpose of assessment

The Annex 57 case studies present a range of different purposes for the individual studies. Examples

include evaluations of early stage design decisions (SE2a, SE2b and SE5), assessments for different

certification or benchmarking purposes (AT studies, DK4, CH studies), comparison of design options (UK5)

and profiling for comparison with operational impacts (NO studies). The purpose of assessment, consisting

of a defined goal and stated intended use, is the first step of an LCA study according to the international

ISO 14040-series as well as the EN 15978 standards. These different stated purposes hence lead to

variations in the subsequent methodological choices about functional unit, scope and other parameters

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made in each study. Standardisation is suggested as a general approach to limiting the uncertainties caused

by choices in an LCA study [74]. However, as exemplified in the Annex 57 case study collection, the stated

purposes of the building EEG assessments vary broadly and cause a wide range of diversity in the reported

studies and results. Hence, a methodological one-solution-fits-all seems possible only on a theoretical scale

although a highly detailed level of standardisation may be appropriate within certain contexts of purpose,

e.g. for national certification, regulatory purposes or building-level EPDs.

3.2.2 Specification of the object of assessment

The Annex 57 case studies reflect a variation of different building types spanning various sorts of offices,

residential single- or multi-family houses, schools and retirement homes. Even though the building type

may point to some functional requirements of the building, this does not give any indications about the

choice of building designs (e.g. high-rise concrete structure or single-storey wooden construction) nor the

technical properties (e.g. thermal performance) that are relevant for embodied as well as operational

impacts. Technical requirements such as thermal performance of the building is directly connected with not

only operational impacts but also embodied impacts caused by material use in order to attain the required

performance. However, reported performances such as “low-operational energy building” or “zero-

emission building” as seen in the case studies, may still be perceived differently on an international scale

due to differences in definitions and due to the different climatic conditions under which the buildings

operate. The multitude of descriptions in the Annex 57 case studies of functional equivalents and physical

characteristics of buildings points to the challenges in describing core functional and technical

requirements as well as physical properties in a uniform and consistent way and thus complicates the

possibilities of comparing studies horizontally.

An additional aspect of the functional equivalent is the reporting of results per m2 floor area, a declared

unit often used in conjunction with the functional equivalent. Even though individual studies may specify

whether usable floor area or gross floor area is the reference unit, these terms may cover slightly different

definitions from country to country. For instance, the heated floor area is in Norway measured to the inside

of the external walls but in Denmark this is measured to the outside of the external walls [75].

Furthermore, national practices may vary as for how to include m2 from parts of the building that are non-

conditioned, e.g. basement or terraces.

The reference study period (RSP) is an important factor for the calculation and reporting of EEG results due

to the relative significance of the recurrent embodied impacts. In the Annex 57 case studies, the reported

RSPs range from 20-150 years and thus present very different perspectives on the temporal aspect of the

assessment. The choice of RSP can be viewed from two perspectives; firstly as a numerical exercise for

16

calculating annualised impacts, an often preferred way to report results of a building LCA. Reported

annualised performance of a building can thus be much misleading depending on the context, for instance

if only the cradle to gate EEGs are included in the assessment. The second perspective of the RSP is as a

parameter reflecting the actual design, where solutions for extension or limitation of the building’s service

life are sought after. This latter perspective is employed in some Annex 57 case studies displaying examples

of embodied impacts from increasing earth quake resistance performance to obtain an increased service

life of building (JP4, JP6) or by adapting the building design to protect weaker components, such as

windows, in order to increase the service life of these (DK3a-b).

As already thoroughly explored in literature, the significance of system boundary definitions to the EEG

results cannot be understated. Standards and scientific recommendations suggests full inclusion of all life

cycle stage processes, or transparency and clear descriptions about potential system boundary

simplifications (such as cradle to gate) [30][13]. However, the Annex 57 case studies show how EEG

assessments in practice operate with selections of process modules across life cycle stages. Only in few

examples do the case studies follow the recommended system boundary types such as cradle to gate (SE

studies) or cradle to site (NO4). The reasons for this disparity between recommendations/standards and

practice may on the one hand be explained by the relatively recent harmonisation of approach. On the

other hand the disparity may also reflect how the defined goal and intended use of the studies vary from

study to study. In this sense, the varying system boundary definitions may each suit their specific purpose

and hence question the very usefulness of a general harmonisation of EEG studies.

3.2.3 Scenarios for the building life cycle

Scenario definitions and the influence on the EEG results are explored from different angles in some of the

Annex 57 case studies, sometimes as part of the goal and other times as part of sensitivity analyses. Case

study (JP7) thus explores different scenarios for the EoL treatment of a wooden house as part of the goal of

the study. Case study (DK1) is an example of a case study evaluating the scenario of the building’s service

life as part of sensitivity analyses.

The relatively long service life of a building implies special attention towards the use stage scenarios that

are relevant to the EEG, in particular the scenarios that describe how materials, components or the building

itself is maintained, repaired, replaced and refurbished. The underlying factors determining the impact on

EEG results of these scenarios can be narrowed down to the scale of intervention and the frequency of

intervention. Replacement of building materials is the most frequently included use stage process in the

Annex 57 studies. A detailed account on the actual assumptions and scenarios for all replaced materials is

not present in any of the case studies, which is to be expected due to the large amount of documentation

17

work this would require. Some studies refer to national guidelines on the replacement frequencies (e.g. DK,

DE and AT studies). However even within one country, assessment practice may be influenced by various

sources for material service life definitions, e.g. by scientific research centres and specific product

manufacturers, thus resulting in significant variations of scenarios applied for comparable buildings and

modelling [72].

Other relevant scenario choices highlighted in some Annex 57 case studies relate to the EoL processes

assumed to take place after the building’s end service life. For specific constructions, some EoL processes

and benefits from next product system may prove to significantly influence EEG results, e.g. in a wooden

structured high-rise building (UK9) evaluating the effect of using a scenario of direct reuse of the wood

(assumed the standard scenario) or a scenario of incineration without heat recovery.

3.2.4 Quantification of the building and its life cycle

The quantification of the building and its life cycle is, in the assessment practice showcased by the Annex 57

case studies, a matter of inventory level of detail and source of data. The access to a high level of detail for

the specific building is based on knowledge that is progressively developed alongside the development of

the building project itself. How this higher or lower level of detail may affect the EEG results can be

evaluated in some of the Annex 57 case studies where the as-build highly detailed inventory (NO4)

contributes to EG results that are notably higher than a comparable building case calculated at the very

preliminary design stages (NO1)[72]. The early design stage evaluations may prompt relevant inventory

simplifications and cut-off practices and hence result in lower calculated EG results as exemplified in some

cradle to gate and early design stage evaluations (see SE2b, SE4).

3.2.5 Selection of environmental data and other information

The differences between and the need for harmonisation of methodology in EEG database sources are

thoroughly discussed in scientific literature. Thus, within each building material database lies a range of

inherent methodological choices, e.g. of data representativeness and system boundaries. The Annex 57

case studies report the usage of 19 different databases. Furthermore, 30 % of the case studies report using

two or more different data sources in the assessments. The choice of database for an assessment may rely

on factors such as availability or apparent geographical representativeness without further considerations

on other specific details of importance to the calculated EEG results, e.g. whether the database considers

carbon storage in wood products. However, this exact modelling detail of carbon storage seem imperative

to the relatively low cradle to gate EG results reported in some studies (AT2, AT5, DK3b, DE2, DE4). When

not balanced properly by EoL processes’ release of the stored CO2, the results of a cradle to gate

assessment can turn negative (AT5) or simply just generate EG results in the lower range (e.g. DK, DE and

18

AT studies) compared with studies using other databases. Hence, when these EG numbers are used outside

context, in simplified system boundaries representations, and without sufficient background explanations

they may result in misinterpretations and misuse.

An additional overall choice regarding input data concerns the use of generic data or the use of product-

specific data in the form of EPDs. The choice of one or the other option may again reflect at which point of

the design stage the assessment is carried out. At early stage design, for instance, the exact knowledge of

the products that are going to be used in the building does not exist and thus generic data is needed for

LCA modelling. However, even for assessments carried out at later stages of the building design where the

specific products are indeed known, it may prove difficult to locate product specific EPDs for all materials in

the building. Hence, generic data or data from other databases is, in the assessment practice, used to fill in

the data gaps, creating uncertainty as to whether system boundaries etc. are consistent in the different

data [75].

3.2.6 Calculation of the environmental indicators

The specifics of the calculation of environmental indicators also lie as inherent choices in the Annex 57 case

studies through the use of specific databases. Of the 19 databases used in the Annex 57 case study

collection, one is input-output based (refer JP studies) and the rest are process based. This modelling

approach in the Japanese case studies thus partly explains the studies being in the higher range of the

reported EEG results.

Although the impact assessment scope of EEG studies focuses on primary energy use and GHG emissions as

indicators, the exact definitions of these indicators can be ambiguous and/or missing documentation, as

mentioned in section 1.2.2. The reporting template of The Annex 57 case studies was not detailed enough

to convey this level of detail for the databases, and not even the background information for the case

studies report the definitions. This in turn could be the consequence of the lack of harmonisation of

indicators as mentioned by Frischknecht et al. [41].

3.3 Points of attention in the use of EEG results

A range of significant, methodological parameters in the assessment practice are presented in the previous

sections 1.3 and 3.2 and summed up in Table 2. It is a deliberate choice from the authors of this paper not

to address the exact numerical influence on EEG results caused by the different parameters, but rather to

identify the points of attention to keep in mind when using EEG studies from external and/or international

sources. The deliberate lack of focus on exact numerical influence is based on the fact that the many

different methodological parameters interact. Hence, the numerical expressions of significance to EEG

19

results will be specific only to the study in question due to the uniqueness of the exact methodological

parameters of study.

Table 2. Summary of the points of attention within assessment practice that leads to differences in EEG results.

Process steps according to EN 15978

Information required, based on EN 15978

Points of attention identified in international EEG literature and practice

Identification of the purpose of assessment

Goal Goal and intended use of study affects subsequent methodological choices, e.g. about functional equivalent, system boundaries etc.

Intended use

Specification of the object of assessment

Functional equivalent Lack of international definitions and terminology to describe functional and technical requirements (e.g. zero-emission-building) as well as referencing units (definitions of m2)

Reference study period Reference study period set: - arbitrarily (as a numerical exercise to report annualised EEG results) - as the required service life of building (although no consensus exists on how to determine this)

System boundaries Variations in system boundaries at different levels: - selection of included building life cycle stages - selection of building model scope

Description of the physical characteristics of the building

Uniqueness of building design and construction practice

Scenarios for the building life cycle Description of scenarios for all periodic operations

Variations in available information on service life of materials and products Variations according to national practice, guideline and/or regulation, for instance: - waste management - building site regulations

Description of scenarios for all included life cycle stages

Quantification of the building and its life cycle

Quantification of all net and gross amounts of materials and products in the building's life cycle

Potential simplifications of the building scale LCI

Type of LCI data Variations in sources and their level of detail (drawings, BIM data etc.)

Selection of environmental data and other information

Environmental data used for calculations

Representativeness of data Generic or product specific data System boundaries of database(s): - including/excluding carbon storage in biomaterials - width of included input and output substances and resources in data's modelling background

Calculation of the environmental indicators

Choice of indicators and characterisation factors

CED definition: - primary or end-use energy - including/excluding feedstock energy - primary energy based on upper or lower heating value of chemical energy sources - point of measurement for renewable energy sources - primary energy content from uranium based energy GWP definition: - included GHG emissions - characterisation factors used for GHG other than CO2 - temporal scope of GHG emissions

Calculation method for total life cycle impacts

Input-output, hybrid or process based modelling approach of data

20

The identified significant parameters of methodological importance summed up in Table 2 are key

elements in order to use, interpret and transfer existing knowledge about EEG profiles and design

strategies in buildings. Research have in several cases advocated for increased transparency in studies of

embodied impacts [13]. With the points of attention described in Table 2, this paper now provides a

structured overview of the methodological choices that is seen to influence EEG results and hence need

additional focus in terms of transparent descriptions.

4 Conclusions and recommendations

In this paper, we systematically explain and analyse the methodological implications on quantitative EEG

results obtained in the Annex 57 case studies and we point to the areas of assessment practice where there

is a need for clarification of the LCA methodological approaches applied in the building sector. The analysis

of methodological parameters is structured by the assessment calculation method provided by the EN

15978 standard. The content of table 2 thus presents an analytical approach that follows the stepwise

methodological choices that are actually made in the building EEG assessment practice. Each of the six

assessment process steps involves one or more methodological choices relevant to the EEG results.

In spite of a thorough standardisation format, assessments in practice are carried out in a multitude of

ways. As exemplified in the Annex 57 case study collection, the stated purposes of the building EEG

assessments are one of the drivers leading to these differences in practice and results. There is nothing

wrong in the differences as such, but it increases the risk of misinterpretations if EEG case studies are used

for inspiration in design practice or even in regulation without taking into account the influence from

specific methodological choices. This shows that a common standard cannot suit all purposes, although it

provides general guidance of practice. For individual studies, existing standards serve well as foundational

guidelines within which to explore the environmental significance of a building and its life cycle. However, a

high degree of detailed standardisation is appropriate for some purposes where horizontal comparison

with other studies is inherent, e.g. certification and in the development of building regulations. Based on

EEG assessments in practice, it is thus recommended to develop standards or guidelines that target specific

contexts of purpose, e.g. national certification or regulatory purposes. These could well be inspired by the

recommendations developed by Annex 57 for uniform definitions and templates which improve the

description of system boundaries, completeness of inventory and quality of data, and consequently, the

transparency of embodied impact assessments.

21

The diversity of EEG study practice impairs the direct use of results for horizontal comparisons or as

inspiration for low-EEG design solutions. The transparency of reported studies is instrumental using the

experience gained and to transfer knowledge to other cases. Furthermore, the transparency needs to apply

to the specific areas of the study that are sensitive in terms of affecting the generated results. In this study,

the methodological parameters which influence to EEG have been systematically addressed and are listed

as points of attention in Table 2. For EEG study practitioners, it is recommended to address these points so

as to ensure the correct understanding and use of a particular case study by a third party. For design

practitioners seeking inspiration for low-EEG building design, it is recommended to evaluate existing,

inspirational studies in light of the points of attention in Table 2 that clarify the choices that may affect

results in a different methodological context. The combination potentials between these many

methodological parameters signifies a multitude of ways in which the outcome of EEG studies are affected.

Further research is needed to determine the quantitative significance of each of the methodological

parameters listed in this paper. In light of the increasing efforts of regulation bodies and the building sector

towards reducing EEG from buildings, awareness of these significant parameters is crucial in order to

interpret and transfer existing knowledge about EEG profiles of and design strategies for buildings. The EEG

resultsand identified methodological parameters presented in this paper will support the informed uptake

of EEG and life cycle considerations in the building and construction sector and lead to the development of

EEG regulation.

Acknowledgements

Part of the work in this paper has been elaborated by the authors as a contribution to the IEA-EBC Annex

57: Evaluation of Embodied Energy and CO2-eq for Building Construction, more specifically for the subtask

4 report on Recommendations for the reduction of embodied greenhouse gasses and embodied energy

from buildings. The authors would like to acknowledge the other Annex 57 experts for valuable discussions

and feedback for project ideas as well as for their direct contribution to the case study collection.

The work was funded by the Danish EUDP programme for Freja Rasmussen and Harpa Birgisdóttir, the

Swedish Energy Agency for Tove Malmqvist, Cambridge University for Alice Moncaster and The Norwegian

Research Center on Zero Emission Buildings (ZEB), partners and the Research Council of Norway for Aoife

Houlihan Wiberg.

22

Appendix A

Case study Database RSP

Product stage

Construction process stage Use stage End-of-Life

Next product system

Main concept Type R

aw m

ater

ial s

uppl

y

Tra

nspo

rt to

man

ufac

ture

r

Man

ufac

turin

g

Tra

nspo

rt to

bui

ldin

g si

te

Inst

alla

tion

into

bui

ldin

g

Use

Mai

nten

ance

Rep

air

Rep

lace

men

t

Ref

urbi

shed

Dec

onst

ruct

ion

Tra

nspo

rt to

EoL

Was

te p

roce

ssin

g

Dis

posa

l

Reu

se, r

ecov

ery

or r

ecyc

ling

pote

ntia

l

Austria

AT1 baubook eco2soft 100 x x x x x New Office

AT2 baubook eco2soft 100 x x x x x New Residential

AT3 baubook eco2soft 100 x x x x x New Office

AT4 EcoBat 60 x x x x x x Refurbished Residential

AT5 Baubook eco2soft 100 x x x x x New Residential

AT6 Ökobau 2009 50 x x x x x x New Office

Switzerland

CH1 EcoInvent 2.2 60 x x x x x x Refurbished School

CH2 EcoInvent 2.2 60 x x x x x x Refurbished School

CH3 EcoInvent 2.2 60 x x x x x x Refurbished School

CH4 EcoInvent 2.2 60 x x x x x x Refurbished School

CH5 EcoInvent 2.2 60 x x x x x x Refurbished School

CH6 EcoInvent 2.2 60 x x x x x x New School

CH7 EcoInvent 2.2 60 x x x x x x New School

CH8 EcoInvent 2.2 60 x x x x x x Refurbished Residential

CH9 EcoInvent 2.2 60 x x x x x x Refurbished Residential

CH10 EcoInvent 2.2 60 x x x x x x New Residential

CH11 EcoInvent 2.2 60 x x x x x x Refurbished Residential

CH12 EcoInvent 2.2 60 x x x x x x Refurbished Residential

CH13 EcoInvent 2.2 60 x x x x x x Refurbished Residential

CH14 EcoInvent 2.2 60 x x x x x x New Residential

CH15 EcoInvent 2.2 60 x x x x x x New Residential

Germany

DE1 Ökobau 2011 50 x x x x x x x New School

DE2 Ökobau 2011 50 x x x x x x x New School

DE3 Ökobau 2011 50 x x x x x x x New Residential

DE4 Ökobau 2011 50 x x x x x x x New Office

Denmark

DK1 PE int 50 x x x x x x x New Office

DK3a ESUCO/Ökobau 2011 150 x x x x x x x New Residential

DK3b ESUCO/Ökobau 2011 150 x x x x x x x New Residential

23

DK3c ESUCO/Ökobau 2011 50 x x x x x x x x New Residential

DK3d ESUCO/Ökobau 2011 50 x x x x x x x New Residential

DK3e ESUCO/Ökobau 2011 50 x x x x x x x x New Residential

DK4a ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4b ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4c ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4d ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4e ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4f ESUCO/Ökobau 2011 50 x x x x x x x New Office

DK4g ESUCO/Ökobau 2011 50 x x x x x x x New Office

Italy

IT2 EcoInvent 50 x x x x x x x x x x Refurbished Residential

Japan

JP2a (Not specified) - x x x New Residential

JP2b (Not specified) - x x x New Residential

JP3 Various 60 x x x x x x x x x x x New Residential

JP4 IO table Japan 60/100 x x x New Office

JP5 IO table Japan 60 x x x x x x x x x x New Office

JP6 IO table Japan 50/100 x x x x New Office

JP7 IO table Japan - x x x x x x x x x New Office

South Korea

KR3 KOR LCI 50 x x x x x x New Office

Norway

N01 EcoInvent 60 x x x x New Residential

NO2 EcoInvent 60 x x x x New Office

NO4 EPD 60 x x x x New Residential

NO9 EcoInvent 60 x x x x New Residential

Sweden

SE2a EcoInvent, BECE 50 x x x New Residential

SE3

EcoEffect, BEAT, EcoInvent 50 x x x New Residential

SE4a

EcoEffect, BEAT, EcoInvent 50 x x x New Residential

SE4b

EcoEffect, BEAT, EcoInvent 50 x x x New Residential

SE5

EcoEffect, BEAT, EcoInvent 50 x x x New Office

SE6

EPD, Ökobau 2013, EcoInvent, KBOB 1 x Refurbished Office

SE7

IVL Miljödata, EPDs, EcoInvent, KBOB, ICE 50 x x x x x x x x x x x New Residential

United Kingdom

24

UK4 BATH ICE, ECEB 68 x x x x x x x x x x x x New School

UK5 ICE, EcoInvent, USLCI 20 x x x x x New Residential

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